College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Int J Environ Res Public Health. 2021 May 30;18(11):5884. doi: 10.3390/ijerph18115884.
The spatiotemporal locations of large populations are difficult to clearly characterize using traditional exposure assessment, mainly due to their complicated daily intraurban activities. This study aimed to extract hourly locations for the total population of Beijing based on cell phone data and assess their dynamic exposure to ambient PM. The locations of residents were located by the cellular base stations that were keeping in contact with their cell phones. The diurnal activity pattern of the total population was investigated through the dynamic spatial distribution of all of the cell phones. The outdoor PM concentration was predicted in detail using a land use regression (LUR) model. The hourly PM map was overlapped with the hourly distribution of people for dynamic PM exposure estimation. For the mobile-derived total population, the mean level of PM exposure was 89.5 μg/m during the period from 2013 to 2015, which was higher than that reported for the census population (87.9 μg/m). The hourly activity pattern showed that more than 10% of the total population commuted into the center of Beijing (e.g., the 5th ring road) during the daytime. On average, the PM concentration at workplaces was generally higher than in residential areas. The dynamic PM exposure pattern also varied with seasons. This study exhibited the strengths of mobile location in deriving the daily spatiotemporal activity patterns of the population in a megacity. This technology would refine future exposure assessment, including either small group cohort studies or city-level large population assessments.
由于大城市中居民复杂的日常城区内活动,传统的暴露评估方法难以清晰地描述大量人群的时空位置。本研究旨在基于手机数据提取北京市总人口的每小时位置,并评估其对环境 PM 的动态暴露情况。通过与手机保持联系的蜂窝基站来定位居民的位置。通过所有手机的动态空间分布来研究总人口的昼夜活动模式。利用土地利用回归(LUR)模型详细预测户外 PM 浓度。将每小时 PM 图与人群的每小时分布进行叠加,以进行动态 PM 暴露评估。对于移动衍生的总人口,2013 年至 2015 年期间,PM 暴露的平均水平为 89.5μg/m,高于人口普查报告的水平(87.9μg/m)。小时活动模式显示,超过 10%的总人口在白天通勤到北京市中心(例如,五环路)。平均而言,工作场所的 PM 浓度通常高于住宅区。动态 PM 暴露模式也随季节而变化。本研究展示了移动定位在推导大城市人口日常时空活动模式方面的优势。这项技术将改进未来的暴露评估,包括小群组队列研究或城市级别的大量人口评估。